As part of DARPA’s Perceptive Agent that Learns (PAL) program, SRI and team members are working on developing a next-generation "Cognitive Agent that Learns and Organizes" (CALO). The goal of the project is to create cognitive software systems, that is, systems that can reason, learn from experience, be told what to do, explain what they are doing, reflect on their experience, and respond robustly to surprise. The software, which will learn by interacting with and being advised by its users, will handle a broad range of interrelated decision-making tasks that have in the past been resistant to automation. It will have the capability to engage in and lead routine tasks, and to assist when the unexpected happens.

In this project, the CIIR will (1) develop techniques to learn to classify and categorize documents according to topic and other relevant properties; (2) Apply learning techniques to predicting what documents will be relevant to a meeting, and (3) Apply techniques to providing a summary of previous interactions with the meeting's participants.

This work is supported in part by the Center for Intelligent Information Retrieval (CIIR) and in part by DARPA through a subcontract from SRI International.